|
|
Absolute deviation, 绝对离差
* b" }; v& P y8 L3 F. z5 g. H, s0 z" {Absolute number, 绝对数; [1 _, X; {1 @# ^ }
Absolute residuals, 绝对残差1 ~7 t& s0 [2 \* f" m8 Z
Acceleration array, 加速度立体阵1 G" |2 x7 c/ L+ K. K4 f
Acceleration in an arbitrary direction, 任意方向上的加速度 V9 B4 N* O; o8 d6 ~& F# n
Acceleration normal, 法向加速度% e' ], e0 m' A4 `2 ?# s7 ^1 ]
Acceleration space dimension, 加速度空间的维数$ g0 w; U( I7 Y4 D h, c
Acceleration tangential, 切向加速度
9 L% p8 N( g5 o( k5 HAcceleration vector, 加速度向量( d; t+ n! n" R. p5 |( e
Acceptable hypothesis, 可接受假设5 d- x# v; L3 v$ f% e. i: C
Accumulation, 累积; X9 o# j7 j, i4 ?6 u
Accuracy, 准确度# r( H& `+ L/ T: Q: {5 Y) w
Actual frequency, 实际频数; c* ?. z8 ?2 Y8 |6 T9 o9 D
Adaptive estimator, 自适应估计量
Q+ Q8 j1 o3 p0 i" F/ NAddition, 相加' h1 s/ t; Z/ d7 l5 Q1 U- |
Addition theorem, 加法定理& P9 \$ R* N1 G" S8 k# P+ e$ x' I
Additivity, 可加性" a( u) y; T; @& Q G6 j
Adjusted rate, 调整率
+ s6 K9 s5 x \& KAdjusted value, 校正值
% X( |2 q1 x6 B' R& `( d Y' X* IAdmissible error, 容许误差, Q' C { ^4 \) V, ? C; o
Aggregation, 聚集性2 d0 s6 T- `6 }/ U. B: t; C3 ?& f' }
Alternative hypothesis, 备择假设- T$ P. U" ~# l8 T3 G
Among groups, 组间
. @ m( r% x: U: JAmounts, 总量! Z6 H5 }: U$ S- Y
Analysis of correlation, 相关分析: l, z- d8 k# O& h( A! R
Analysis of covariance, 协方差分析
& C1 C0 F' x8 _ ~Analysis of regression, 回归分析
! m9 P; L1 u! NAnalysis of time series, 时间序列分析- O6 m) |* p$ I, x* M9 G
Analysis of variance, 方差分析( d: p) }7 I( X0 }$ j& \! }
Angular transformation, 角转换
2 r8 y3 E' {0 G: H7 W& n# A$ aANOVA (analysis of variance), 方差分析
3 i0 p# a+ t9 T1 I& o0 _- vANOVA Models, 方差分析模型
" f, T Y' _: s" Z! zArcing, 弧/弧旋3 a: F) ?" f" A7 u" c
Arcsine transformation, 反正弦变换3 ?: n1 H1 x! h+ b! z
Area under the curve, 曲线面积9 G- x8 W: v0 \; @3 q% O# ]" P
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
! F$ Y& u0 K7 [7 F$ X1 ]ARIMA, 季节和非季节性单变量模型的极大似然估计
5 M, x: O6 g. \7 ]Arithmetic grid paper, 算术格纸
8 Z% a( X. L. ^4 T5 o+ D3 MArithmetic mean, 算术平均数
0 `- U- {0 {5 mArrhenius relation, 艾恩尼斯关系7 z7 X! p: c5 C1 K
Assessing fit, 拟合的评估+ u% c9 q# l# B( \6 D! p4 j
Associative laws, 结合律
6 z( o4 ?) b, T- `) E4 EAsymmetric distribution, 非对称分布
0 M# H: u( H( o6 b: \) PAsymptotic bias, 渐近偏倚
: g3 m$ k8 W tAsymptotic efficiency, 渐近效率. i% M! X- G$ {& q
Asymptotic variance, 渐近方差( Z0 M1 b* M% h. v4 l
Attributable risk, 归因危险度; B3 `& U0 D B6 ^$ N! y
Attribute data, 属性资料
( u a: t/ @2 `& x. u5 ]6 uAttribution, 属性' U9 H5 I# v# c' y$ D" @( I
Autocorrelation, 自相关
$ b$ S- B% F" a% rAutocorrelation of residuals, 残差的自相关
4 N3 K6 z* f+ ?5 h4 ZAverage, 平均数7 P+ s) _ u+ T0 [* X
Average confidence interval length, 平均置信区间长度
7 h Q# I' E4 eAverage growth rate, 平均增长率# o7 C/ e$ {' |& z. [( u
Bar chart, 条形图% p% Y! t5 Q3 Q, V) @3 v5 J
Bar graph, 条形图+ b( ?1 ]- j- y. H# H" y
Base period, 基期
+ q( L6 g$ Y0 h/ r9 w. {Bayes' theorem , Bayes定理2 y; o( Y2 G* w' a
Bell-shaped curve, 钟形曲线
. j% T% K$ a4 \4 ~0 A3 K$ j. @1 ABernoulli distribution, 伯努力分布
7 m& w* l- I* KBest-trim estimator, 最好切尾估计量- ~1 K! } {5 ]* o! o, g
Bias, 偏性* v8 Z4 x9 y7 b& u
Binary logistic regression, 二元逻辑斯蒂回归/ Y: a- e+ D# T2 f( [
Binomial distribution, 二项分布
7 W; s+ J7 h- j8 G' W; o/ ^Bisquare, 双平方! p1 u$ ] R+ _& o1 ^
Bivariate Correlate, 二变量相关& N. w/ D* ]2 _& @6 v
Bivariate normal distribution, 双变量正态分布& {% M% D/ O7 Y/ y; o5 I: u) a
Bivariate normal population, 双变量正态总体: _ R) ?, ]% d
Biweight interval, 双权区间2 B& W! k2 N( o2 s. o
Biweight M-estimator, 双权M估计量
) Q, h/ m2 k* DBlock, 区组/配伍组
, O% U0 m& O7 \6 U. q( p( a' `BMDP(Biomedical computer programs), BMDP统计软件包3 |/ Z' j) R" X2 b/ a8 i
Boxplots, 箱线图/箱尾图
0 n$ I7 D% @5 GBreakdown bound, 崩溃界/崩溃点' k/ L3 b+ U; V# S' i
Canonical correlation, 典型相关2 c8 J" C8 f% |& C: Z
Caption, 纵标目
* T) ~6 C9 E1 V* p" \: nCase-control study, 病例对照研究) q/ l% i' L+ s0 w+ ?* r
Categorical variable, 分类变量; u5 J2 r$ M; V
Catenary, 悬链线0 W/ D; L x G# i! V) K2 w M. n
Cauchy distribution, 柯西分布" G7 r6 T3 S- Q Z8 _
Cause-and-effect relationship, 因果关系/ k, @/ u$ F' j; T. V! z5 Q
Cell, 单元
/ [7 D$ o. `7 d% k. S+ ~Censoring, 终检% g+ Y' O4 u+ B
Center of symmetry, 对称中心
; a7 k9 t( @# S5 A) x6 ~Centering and scaling, 中心化和定标
& k, B C) D( L) N& i5 ^Central tendency, 集中趋势$ }- O3 X& x) a' U( R
Central value, 中心值/ x* c( i g8 \) j+ {& j
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测8 H: {# A2 H3 s s! G- N
Chance, 机遇
9 G( Z; _0 G. P% h+ R: D! i- wChance error, 随机误差8 Z1 o; K/ u5 `5 s% c* ?- Y
Chance variable, 随机变量4 D- N" |0 G1 R
Characteristic equation, 特征方程
! X2 m4 N% ]4 a- o' mCharacteristic root, 特征根
- d6 `. f6 q {" S1 M9 {, @Characteristic vector, 特征向量
7 C' F' I4 d) \6 |Chebshev criterion of fit, 拟合的切比雪夫准则; T* L ~: l! I3 O/ E6 B
Chernoff faces, 切尔诺夫脸谱图
0 `* y, M- o& U* I0 X4 lChi-square test, 卡方检验/χ2检验
6 `5 c" T4 X4 w) v/ A4 ECholeskey decomposition, 乔洛斯基分解* X4 y" }, G, m+ [& q6 e2 `4 m- H! d$ i
Circle chart, 圆图
# P9 x. T/ `- W0 GClass interval, 组距 O/ s. e. T1 h. `9 w3 b7 b; y6 n% L& r
Class mid-value, 组中值
g) x$ _5 E% RClass upper limit, 组上限/ L) ]$ `! K0 V2 u
Classified variable, 分类变量
! D t& }8 }; |* T$ TCluster analysis, 聚类分析
+ d% `" t" u/ @$ MCluster sampling, 整群抽样
5 d! D, Y0 |% V- i& E) |Code, 代码
# I O0 u9 D5 [% t& uCoded data, 编码数据+ K" I* Z/ T: [- ?
Coding, 编码8 `8 I' c! D8 F7 M& a
Coefficient of contingency, 列联系数+ x: e2 T$ B9 C0 K/ e
Coefficient of determination, 决定系数0 `9 @( y1 O0 B$ T7 G4 ]
Coefficient of multiple correlation, 多重相关系数9 [. l/ S' P! J+ T; ]- M
Coefficient of partial correlation, 偏相关系数
# x& T3 R% X: v. sCoefficient of production-moment correlation, 积差相关系数
! T6 w$ G! ~+ t4 f% E4 E# \1 ACoefficient of rank correlation, 等级相关系数4 w3 K4 X' q4 E- W- F. [
Coefficient of regression, 回归系数. K8 L* [) {; y( `& L5 k
Coefficient of skewness, 偏度系数
5 v9 E6 X% O/ }* j$ RCoefficient of variation, 变异系数
Y* u" |! k" g! I6 W$ ]Cohort study, 队列研究" V5 g6 H3 v4 {' s% v, y
Column, 列
! t; t4 |3 l# ~5 u6 [7 mColumn effect, 列效应6 e3 I, j. C; m( [8 H& `/ {
Column factor, 列因素! O# f7 m: G+ h' B
Combination pool, 合并+ _" V. S4 v9 G7 w) B0 ]5 T
Combinative table, 组合表- f1 w( ]# c" \) R8 Q
Common factor, 共性因子
6 O1 H$ u% p0 k) a$ VCommon regression coefficient, 公共回归系数
7 U+ R; h$ w, V, [. TCommon value, 共同值
/ m5 r# P& `+ r7 m( }. ?; X7 H/ jCommon variance, 公共方差3 i" Z8 Q) p* {- g" r0 W# j! @
Common variation, 公共变异' S1 U8 @/ j: k/ ~2 }5 N- l
Communality variance, 共性方差$ P4 v) `3 {8 t. W) ~# P
Comparability, 可比性. B t$ _& z- r' W$ x! b# e; u
Comparison of bathes, 批比较' H9 U# f2 t% u7 \9 t
Comparison value, 比较值
5 N: S: }4 q. _. s+ O# a# K* dCompartment model, 分部模型5 O- h/ i7 U+ H8 n! _, |- f) p
Compassion, 伸缩
# @1 M" w2 j k/ X2 @ q' ~* zComplement of an event, 补事件
$ h. l! V" D# v/ EComplete association, 完全正相关
/ p8 z8 x4 l% F, WComplete dissociation, 完全不相关; u. w: \3 V5 S# a: n
Complete statistics, 完备统计量, ]( o, G/ _7 B O1 I# P: Z% J) a
Completely randomized design, 完全随机化设计
7 G4 s( I# ^6 u0 e) BComposite event, 联合事件
5 I1 Q" q0 [" f& \' ? }Composite events, 复合事件# {' V2 d( i% o5 [' V, `& ~5 W; H
Concavity, 凹性
. w4 G, b9 s8 w7 | M \Conditional expectation, 条件期望
2 j8 a) \9 b0 J8 iConditional likelihood, 条件似然2 M+ e- U) {! m$ B# F! o
Conditional probability, 条件概率* H% ^5 ~% `6 p; J
Conditionally linear, 依条件线性: G! O1 ~+ h, A& B" a% k
Confidence interval, 置信区间
: Q: {1 ?6 g& k6 h& r% w7 VConfidence limit, 置信限$ f; S$ q: v0 l- F' l
Confidence lower limit, 置信下限
5 G* ^/ N5 C6 l' B2 W6 M0 q7 b/ VConfidence upper limit, 置信上限
" C& u" [9 ~* T5 P5 D3 {* ?Confirmatory Factor Analysis , 验证性因子分析
5 ]9 Y! t: q- T; i1 o; G0 OConfirmatory research, 证实性实验研究/ n# p8 x5 j& B; L+ E% g# G6 c8 `, s1 A
Confounding factor, 混杂因素* K( S$ m: O( z& l9 y
Conjoint, 联合分析* f$ K+ p3 g4 F$ f' k6 D
Consistency, 相合性. _6 q" L" J, V5 J$ n0 X
Consistency check, 一致性检验8 q# w1 A$ O) ^' r. }, p
Consistent asymptotically normal estimate, 相合渐近正态估计
" Z$ q6 L3 k8 v% T' h0 g3 jConsistent estimate, 相合估计6 c* Y5 ^4 X0 B! [' s! `
Constrained nonlinear regression, 受约束非线性回归9 d9 ^! k, \4 k: B3 v$ _
Constraint, 约束
/ ]1 }6 Z0 L3 ~# F+ {Contaminated distribution, 污染分布
! O& y6 f; v6 t/ `) s- XContaminated Gausssian, 污染高斯分布
' k( X; n# n% M% X" EContaminated normal distribution, 污染正态分布
7 E3 ~$ } m! Q* w0 kContamination, 污染
/ j. C9 a/ g$ a5 hContamination model, 污染模型
0 V6 U# Q* l/ | p/ K) _Contingency table, 列联表
6 O: P4 h+ d. C6 ?, D eContour, 边界线2 i$ D* n$ Q6 A2 n
Contribution rate, 贡献率
! I+ v1 Z: g+ MControl, 对照( G- S {$ w/ n1 L4 r
Controlled experiments, 对照实验
! F, m# p. q, o: V8 mConventional depth, 常规深度
/ h | H5 v1 F) }3 N( _$ c+ yConvolution, 卷积0 i8 I+ {, J6 N
Corrected factor, 校正因子
* t, i0 F1 X2 }* A. V& k. YCorrected mean, 校正均值
( y& ]' h1 D0 T) J. R( DCorrection coefficient, 校正系数
1 I! r0 a1 \- M# T% F, ?Correctness, 正确性
. f/ _% }( i3 Q0 M1 DCorrelation coefficient, 相关系数; ?( T( k9 s' G) J
Correlation index, 相关指数 j+ ^ T3 {8 z" @2 L3 Q: @
Correspondence, 对应
1 G; Y; z: E, w5 qCounting, 计数; S/ x5 e6 `& t
Counts, 计数/频数! T2 a# V- x7 P0 e# i. s* X
Covariance, 协方差
2 H8 }, k" T u4 B5 bCovariant, 共变
; x' }4 i5 ~5 }; R; E2 wCox Regression, Cox回归
# f, [$ v6 k4 L/ mCriteria for fitting, 拟合准则5 E3 a% I9 P8 \8 K0 j" G1 E; Z1 S
Criteria of least squares, 最小二乘准则; `" g: L& I' W
Critical ratio, 临界比- Z& f, I. l( M5 x
Critical region, 拒绝域6 `4 E% K$ q* D, Q& D- E
Critical value, 临界值
4 `0 a$ N3 w& `Cross-over design, 交叉设计
! ^+ T6 }! l r2 Q9 GCross-section analysis, 横断面分析) D h ~$ A6 N% }' W7 ]: \
Cross-section survey, 横断面调查 U _+ o9 C4 P/ Y9 S8 P
Crosstabs , 交叉表 ! A0 ~9 y1 Z5 i! C+ p6 L9 ]; J
Cross-tabulation table, 复合表) `7 D' ?- n1 Y
Cube root, 立方根
2 q" W" G, o& u8 s! A! g6 DCumulative distribution function, 分布函数4 ]% |" i9 R$ K
Cumulative probability, 累计概率, a/ T) c; B+ C, j, s
Curvature, 曲率/弯曲# ~4 Y3 _+ V6 Z& b. b
Curvature, 曲率
! D5 F) T' C6 P8 F) T' ]4 I! i0 GCurve fit , 曲线拟和 & z; u* d# [) J# a9 S9 D3 q" |, \
Curve fitting, 曲线拟合* A) {; M9 v" E& U0 B9 E7 w7 U
Curvilinear regression, 曲线回归
o4 h3 i& T4 ]Curvilinear relation, 曲线关系
: p' w' K: Y% O; QCut-and-try method, 尝试法
& Z1 v5 L+ o: d2 a& ?6 ]; ECycle, 周期2 o9 U# B) x; H7 Z; @
Cyclist, 周期性* \9 D& ~+ j% r* c% z1 O# [8 _
D test, D检验. [( r$ `! z7 w5 m8 p3 n4 z
Data acquisition, 资料收集0 t: A& A( ]1 R# D1 L* @
Data bank, 数据库
' Y f7 y: y9 E- @+ x$ LData capacity, 数据容量# L& x2 J. z/ p, v. p0 T# `
Data deficiencies, 数据缺乏
L: n* `* D- }# Q# j, J+ GData handling, 数据处理
1 \* l& l. o. R8 N- eData manipulation, 数据处理
' R# j1 ]( _8 l* e4 RData processing, 数据处理
: d( Z% N$ W( ]& u, f# OData reduction, 数据缩减
1 R0 h! m' |% o+ T7 V6 K- eData set, 数据集
- p( r9 d. v9 y- C; Q/ x' LData sources, 数据来源/ v, N" u+ k8 M/ y
Data transformation, 数据变换
( s# V( G2 S {" I- S& ` CData validity, 数据有效性
4 b2 ~% b, `! @7 P, m$ rData-in, 数据输入) l ?! {' R! u
Data-out, 数据输出: Y6 s+ v2 R" A& V
Dead time, 停滞期' b# @5 U! T/ x& C1 n
Degree of freedom, 自由度: ~5 \: r& b! _8 B. x
Degree of precision, 精密度
% v: e& N* R, ?% Z6 |Degree of reliability, 可靠性程度
/ V: A+ w" M/ k. `" j, Q* {5 MDegression, 递减
0 @8 X( p4 K4 C: p. B) U1 |6 o. uDensity function, 密度函数8 B: |4 ~9 E7 O+ w$ V9 D
Density of data points, 数据点的密度
9 I* C/ B9 ~) p. M4 j6 m2 GDependent variable, 应变量/依变量/因变量
" u0 w3 ]- h- V! ]7 P) K5 B- L DDependent variable, 因变量6 e' s6 N: w7 x) `
Depth, 深度! H6 s) i; a+ P4 o( A+ |$ K
Derivative matrix, 导数矩阵+ d3 z6 v; V, d& M
Derivative-free methods, 无导数方法- q4 ~/ o% i1 T
Design, 设计3 D" _. n0 \- v: R
Determinacy, 确定性, B) G: e& [) j0 i r
Determinant, 行列式
5 `/ N) o* Q/ Y( I/ KDeterminant, 决定因素! l) U, r+ p( [4 O0 U* k4 B
Deviation, 离差/ \; F& G5 Z/ o
Deviation from average, 离均差
+ T4 Z0 V. h; [, \0 h/ k* X' qDiagnostic plot, 诊断图
+ L3 c1 g- m9 [8 m& x: XDichotomous variable, 二分变量
; N$ d- ^! T. [. i* _0 Z/ UDifferential equation, 微分方程
- _* z6 N$ R1 C% o) nDirect standardization, 直接标准化法
* [+ d V' s% u+ Y) V8 PDiscrete variable, 离散型变量/ k* K4 I' q7 N7 h; P" p
DISCRIMINANT, 判断 8 L0 l+ Y2 }4 [. b6 W' y' z
Discriminant analysis, 判别分析
( t q! R) X; y: Z! aDiscriminant coefficient, 判别系数+ O1 ^* V6 k. l! K( {9 b% X
Discriminant function, 判别值
! n/ p" j* ]1 q+ `! ZDispersion, 散布/分散度
6 B2 w7 g5 V, G$ m. iDisproportional, 不成比例的
* s) y; r9 {" D3 b, A5 a) X( DDisproportionate sub-class numbers, 不成比例次级组含量
" V% @9 @/ t* KDistribution free, 分布无关性/免分布: E* `1 d! Y3 l$ F
Distribution shape, 分布形状% h) ^, a( U# A- J
Distribution-free method, 任意分布法' _* t, s- [% {3 l* z2 y. ]
Distributive laws, 分配律5 d" j$ K* i, A( L) M# D" y# |: o
Disturbance, 随机扰动项
G9 `8 S# z% |1 QDose response curve, 剂量反应曲线; L6 ?% ~. {9 r* ^% D T' O: _
Double blind method, 双盲法! c* f3 s+ q2 Z8 p7 d# q
Double blind trial, 双盲试验0 b8 X( L' H# H' d+ Y: L
Double exponential distribution, 双指数分布2 H. W1 t# r5 ^# ]. ^. f' P+ q
Double logarithmic, 双对数
6 a5 V: {2 R" L6 SDownward rank, 降秩
7 i2 z! i1 ]# \$ L" JDual-space plot, 对偶空间图
; i; i( K1 n7 N0 X* W8 c6 t: i* P. y9 \DUD, 无导数方法& |5 ~, l6 I M8 h* W
Duncan's new multiple range method, 新复极差法/Duncan新法
7 n+ G2 a9 ^; U& E/ ]. PEffect, 实验效应2 _! t9 O% i5 N. s6 w- d; o) f
Eigenvalue, 特征值- w/ S8 o* v$ q* P; x( n( [: S
Eigenvector, 特征向量# e. R$ ?+ I& S- ^
Ellipse, 椭圆
1 f2 k" R$ ?* \) }( VEmpirical distribution, 经验分布
0 O2 f0 f7 D) Y5 i( yEmpirical probability, 经验概率单位8 k0 E& q$ M1 t, l+ f* [
Enumeration data, 计数资料: W" x( b4 c4 u! f
Equal sun-class number, 相等次级组含量
V2 c0 c1 b/ n, Z6 b* {Equally likely, 等可能8 y: @) g+ H- e4 u m8 B2 p
Equivariance, 同变性9 S; J; ^- J9 f4 T8 A* j9 T
Error, 误差/错误
- D1 J" v. B. K( e$ KError of estimate, 估计误差
. Z- F" w% | U: `! Y* \5 J) ~' @' gError type I, 第一类错误
; Z0 t( s- L6 N9 U( F2 O oError type II, 第二类错误
8 k2 C9 ^2 A6 `- F' aEstimand, 被估量( y) d b7 J/ e
Estimated error mean squares, 估计误差均方- o* |: e8 A& [0 _3 m
Estimated error sum of squares, 估计误差平方和1 w ?0 b8 I2 ^0 E4 O. H( ]
Euclidean distance, 欧式距离
" d6 D. T9 F4 d' ^Event, 事件
5 n9 I B6 J' p# tEvent, 事件" K6 `7 ^6 R: L$ @6 |1 e/ `
Exceptional data point, 异常数据点
$ e7 d- R; E' f8 MExpectation plane, 期望平面, ?3 m( G/ p3 X R5 `
Expectation surface, 期望曲面
" K; n0 Y) O) H) \0 e! ~Expected values, 期望值. v7 @1 L) Y W: O1 G* K
Experiment, 实验1 {$ g' I; Y: v' q! \2 S$ e1 T, o
Experimental sampling, 试验抽样
& X: o( F" h& N+ m& f" fExperimental unit, 试验单位 C( e1 n* g5 U- A0 o7 F
Explanatory variable, 说明变量# s4 I3 H) q1 `6 ?, j; A
Exploratory data analysis, 探索性数据分析
' v$ H' j- `& \7 tExplore Summarize, 探索-摘要
1 O, j+ C& P5 }* j( {* ?Exponential curve, 指数曲线, ]6 z5 O% Y' ~1 d) P
Exponential growth, 指数式增长+ |1 N, P+ ]) q. P( a/ Q
EXSMOOTH, 指数平滑方法
& q/ _+ y {1 ZExtended fit, 扩充拟合
) d0 `. P0 |3 M! N! j, l8 YExtra parameter, 附加参数0 i, m* I+ e! T. n, K
Extrapolation, 外推法) f; Q8 G( [" d5 A( T
Extreme observation, 末端观测值
/ _8 S) X' D5 z5 u* ^; M1 I4 HExtremes, 极端值/极值
4 i6 L9 U. ~# L9 KF distribution, F分布
7 A# [8 S) e) [) |6 ?F test, F检验( S z" Z: v4 @8 q) F
Factor, 因素/因子) T1 @4 q) o; G8 _3 G; \8 [
Factor analysis, 因子分析- C9 R* M' p) B8 M0 X; \
Factor Analysis, 因子分析
* J9 L3 c7 _+ B. p1 L# wFactor score, 因子得分
5 s5 J: a. G; v$ ^1 {3 tFactorial, 阶乘% p( w+ w# k1 ]& G; ]" k& v
Factorial design, 析因试验设计
$ R1 e& i% J- p; CFalse negative, 假阴性. Q, V( U O+ v2 H/ o" ^
False negative error, 假阴性错误
8 K$ A. u* n: i) T wFamily of distributions, 分布族
. P" D. X! a m. j8 tFamily of estimators, 估计量族4 v1 K0 m* f3 k% G% m
Fanning, 扇面9 A) ~! ~* y8 g
Fatality rate, 病死率
( P% d7 z% ^- D* K( IField investigation, 现场调查- k# T& `/ e1 C. i) d7 K3 j
Field survey, 现场调查
! W- S- \5 [3 }% T a0 H9 p; n) CFinite population, 有限总体
. J4 _$ }" x/ J' J5 F( O2 AFinite-sample, 有限样本5 ?% U+ ?1 p' q0 C6 p4 `4 c9 V. p
First derivative, 一阶导数
, P6 G* T0 y/ Q) U: s7 eFirst principal component, 第一主成分
4 i/ `- U- L% O6 X/ c& QFirst quartile, 第一四分位数" G' w0 C0 B+ E9 w3 O: B. X
Fisher information, 费雪信息量8 ?6 ~2 z) {8 g
Fitted value, 拟合值
0 d5 X, N# P2 `" i0 s6 qFitting a curve, 曲线拟合+ n8 K" X! M9 Y( v7 O+ S) k
Fixed base, 定基9 f9 R% y' H# h* t1 X G
Fluctuation, 随机起伏0 h- i# y' a( O7 ?4 h6 u9 \# ]
Forecast, 预测2 \5 y8 o- Q* w' w
Four fold table, 四格表" G) s7 B' V$ ?" \# D Q
Fourth, 四分点/ C5 D: Z- E1 ?9 ~4 J' k. g
Fraction blow, 左侧比率
3 l& t" Z: H, z5 _' g8 LFractional error, 相对误差' E3 U, n/ P3 D- L
Frequency, 频率( Z, M- Q8 p( f" U1 G
Frequency polygon, 频数多边图
3 w, ~( N0 Q0 V6 i( gFrontier point, 界限点
@. ^- w0 @! x5 [ v5 T) L0 N8 OFunction relationship, 泛函关系
1 W1 G% P1 Q f& BGamma distribution, 伽玛分布! y% @+ R9 j E
Gauss increment, 高斯增量. h0 q! x1 f7 U3 L) n4 y! \( L& s
Gaussian distribution, 高斯分布/正态分布5 O2 @ X1 {' {
Gauss-Newton increment, 高斯-牛顿增量5 H4 F9 ]* T9 I* \! C; I0 e
General census, 全面普查
9 V* u/ k& @3 d$ zGENLOG (Generalized liner models), 广义线性模型
: G6 h8 k7 F* m3 e" m* iGeometric mean, 几何平均数
: W7 p3 [, H2 RGini's mean difference, 基尼均差
8 E4 w- A' f% O" JGLM (General liner models), 一般线性模型
9 n3 C% T1 h/ D; \4 m5 c1 X9 pGoodness of fit, 拟和优度/配合度
# g) S5 X9 }* u4 e# J0 c. j* YGradient of determinant, 行列式的梯度' G9 l0 Z# e7 H$ p' i- O# ~
Graeco-Latin square, 希腊拉丁方 a7 o3 ]6 N5 r, ?, A0 y
Grand mean, 总均值2 N+ D6 Q, |+ D" G9 O
Gross errors, 重大错误
2 V# o/ d" L( K! o0 `- s/ H3 sGross-error sensitivity, 大错敏感度
! T" }$ O0 z5 q) ]Group averages, 分组平均
: q' [9 m8 h+ Q) FGrouped data, 分组资料( O: L) Z4 E; P( c9 ?
Guessed mean, 假定平均数% t# _0 c/ ~: L* V5 }$ H
Half-life, 半衰期* x; k4 ?4 j9 g
Hampel M-estimators, 汉佩尔M估计量% l4 F' h; y" K3 X3 V$ F' L
Happenstance, 偶然事件" m" p4 Z! P3 Q2 l$ c8 u
Harmonic mean, 调和均数
* T, m0 |+ @4 n- ~+ eHazard function, 风险均数
. X& v6 g9 g/ d. bHazard rate, 风险率
1 z! n* x/ E5 E m" YHeading, 标目 : P/ U, O8 m# v: n
Heavy-tailed distribution, 重尾分布$ m) ~ m. n1 x4 }- w( N# b) {7 I
Hessian array, 海森立体阵
6 ^0 T1 p3 r+ ^Heterogeneity, 不同质
& t3 X7 a- f. WHeterogeneity of variance, 方差不齐
, w- V6 p+ Z; X% X* n7 G" b3 dHierarchical classification, 组内分组8 }: _$ |8 }, H* \4 _) q
Hierarchical clustering method, 系统聚类法# m0 u' y) v5 @7 {+ Y- M
High-leverage point, 高杠杆率点2 T* _3 U) \$ r+ S0 V! z' I* O
HILOGLINEAR, 多维列联表的层次对数线性模型5 \2 _) ]% [4 I) q, K- `1 s
Hinge, 折叶点
7 E2 i# h7 M7 nHistogram, 直方图; R, w6 V- v& q
Historical cohort study, 历史性队列研究 . x/ h0 u& k O% r( H. k
Holes, 空洞/ v, b8 j3 @( T4 k. A! J+ y7 r8 D3 y
HOMALS, 多重响应分析( u4 z3 w m c% A" _
Homogeneity of variance, 方差齐性
& r' D+ w9 Q2 oHomogeneity test, 齐性检验$ e# `" x" e: E: \! E
Huber M-estimators, 休伯M估计量
8 z q1 ?7 r- j/ K9 p$ F7 g! EHyperbola, 双曲线( A, Q0 B/ _4 o9 x% o; B* J& l
Hypothesis testing, 假设检验
+ V5 e5 {" T) i$ [Hypothetical universe, 假设总体6 t- Y$ G# U/ i* _ `
Impossible event, 不可能事件( i! c: [4 P+ G. U4 t6 T
Independence, 独立性
* v% O5 Z, ], k0 e. Z3 }& D+ ]5 V+ wIndependent variable, 自变量
2 d% ] D. ~ I% d: h, rIndex, 指标/指数+ C) ~3 x# J" U1 U8 B. O% Q3 a
Indirect standardization, 间接标准化法0 U; z6 b7 a' P1 }+ j; |1 N+ i
Individual, 个体
! G- o: p/ j) H$ [1 qInference band, 推断带# N# v' ~' s' L1 I& H- U
Infinite population, 无限总体. e- X0 u0 L3 m
Infinitely great, 无穷大
8 ^. v* z# Y3 R+ E# |& j$ tInfinitely small, 无穷小
) _0 p2 W3 U( C. }) y2 h8 ^Influence curve, 影响曲线
* [+ F$ ^ d) ^0 E' aInformation capacity, 信息容量3 J2 Q; a* [# i( P; U5 M; i
Initial condition, 初始条件
1 R" r. T; L/ j1 S/ Q0 [# kInitial estimate, 初始估计值2 Q7 x: m0 u5 M" M, b0 k
Initial level, 最初水平
1 F6 N& E# j9 xInteraction, 交互作用6 z( J t1 m) N
Interaction terms, 交互作用项1 @6 D% B/ K$ Z
Intercept, 截距
+ n' F4 U) b2 F _3 O) H0 I; GInterpolation, 内插法
0 r# E1 @- a% e1 L3 j# lInterquartile range, 四分位距9 @ `: {4 I) b4 X$ q
Interval estimation, 区间估计& y) ^1 `0 b7 u! s
Intervals of equal probability, 等概率区间6 o( I2 x* p4 i8 h1 b9 z- [
Intrinsic curvature, 固有曲率
" `, C1 O5 g: i: SInvariance, 不变性; E* @9 r* Q& q* G& h9 f0 I) b0 k
Inverse matrix, 逆矩阵
3 T: F4 k" S% y8 @; i: |8 d0 `Inverse probability, 逆概率
7 S" h! M/ a: p4 j! gInverse sine transformation, 反正弦变换
! d# _ I: X# i8 |1 d. IIteration, 迭代
: x! ?$ Z9 ?3 E- U+ q* {5 NJacobian determinant, 雅可比行列式6 I( R; P0 ]1 e" h
Joint distribution function, 分布函数& B4 }9 Z4 J5 N: }9 X
Joint probability, 联合概率
8 `! A& ?5 L, @, e0 |Joint probability distribution, 联合概率分布& r/ D0 T. ]7 B' j3 v
K means method, 逐步聚类法
5 x6 X# z7 r" Y: `4 m# v+ XKaplan-Meier, 评估事件的时间长度 0 k2 |+ ^5 N3 ^3 ]- e% I
Kaplan-Merier chart, Kaplan-Merier图
7 ]5 q$ ]( _! b3 X& c3 w0 ^7 ]Kendall's rank correlation, Kendall等级相关
# f5 E9 z. M0 k6 H: {9 x hKinetic, 动力学
6 e* n/ B! ^9 D7 o: J4 s& fKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
" m4 Y- U) I, }9 ]# I7 EKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验4 d- g( A! c7 Y( {
Kurtosis, 峰度
" H: t3 e- A5 r: ~+ Z& b) `4 NLack of fit, 失拟
8 p5 F/ f$ j ^/ N7 |Ladder of powers, 幂阶梯
4 z7 S& q4 L: O v, x8 MLag, 滞后7 z7 X3 {) I3 |+ p0 M- g, ]
Large sample, 大样本" o# j, r! ~' M: O/ r
Large sample test, 大样本检验
% n9 p. K7 [: }7 d! T; u, xLatin square, 拉丁方
1 ~3 J& y! b2 ~8 \Latin square design, 拉丁方设计
& M- L' I& @' i% SLeakage, 泄漏# }7 s! p [- E5 {4 [) ^
Least favorable configuration, 最不利构形3 s6 _* I/ u4 Z, l- [
Least favorable distribution, 最不利分布
7 T6 D# U" r# q; X) E2 e. @Least significant difference, 最小显著差法
7 `! j0 W, x4 t, E, h" HLeast square method, 最小二乘法0 f: K3 P1 j% @
Least-absolute-residuals estimates, 最小绝对残差估计2 ^9 o% o5 m1 z& l" X) o9 x" U
Least-absolute-residuals fit, 最小绝对残差拟合
+ i ]* a* x0 PLeast-absolute-residuals line, 最小绝对残差线
5 A! \& \) Z' ~0 c# K+ C; S8 C; [Legend, 图例' J; J5 @/ `% T$ K7 I: `. f# m
L-estimator, L估计量: S7 T3 z( D) `
L-estimator of location, 位置L估计量# m- {; ~; t' R' {" i f8 G
L-estimator of scale, 尺度L估计量( Q$ | B. r6 D3 J+ j, D
Level, 水平
1 q1 i& @2 g4 A D: RLife expectance, 预期期望寿命 h# s" i( _% a; {. Z9 a$ M
Life table, 寿命表. Z1 t% c5 j9 h
Life table method, 生命表法8 U T9 \0 H) b# U6 M+ _/ U
Light-tailed distribution, 轻尾分布
W9 ~3 \& p) [2 w' MLikelihood function, 似然函数. j5 P6 x. P7 E
Likelihood ratio, 似然比7 ?- ?+ b2 w4 Y* w* n6 v
line graph, 线图/ O* |* Y- H- J
Linear correlation, 直线相关
9 s, S h' e: W* N; f) s6 X' WLinear equation, 线性方程9 P& x& o7 {! }2 W
Linear programming, 线性规划% `$ G; _/ o* k( {- M$ t
Linear regression, 直线回归! }- Q6 K1 v7 z) {* I" r
Linear Regression, 线性回归# O7 S" k6 y" f/ n8 I. M" i7 o' p( I
Linear trend, 线性趋势5 q; J: y ~! q! M h
Loading, 载荷
: d$ y5 }% X: K) V9 FLocation and scale equivariance, 位置尺度同变性 {& b. U1 {& a5 N) S3 _& @, S
Location equivariance, 位置同变性
4 B& H: D) [: @3 g' BLocation invariance, 位置不变性. s, n1 A4 X s( q
Location scale family, 位置尺度族
. B4 ^1 q' o9 iLog rank test, 时序检验
! u2 |% I& W% V* ^1 s! l# M3 qLogarithmic curve, 对数曲线
- r1 O' G1 @4 @" ?4 ~/ G& ALogarithmic normal distribution, 对数正态分布3 ^& c1 }0 O, s8 R' n) V1 x" x
Logarithmic scale, 对数尺度9 Q% m! q) v$ N
Logarithmic transformation, 对数变换
. n1 v4 |5 y8 V" J! ~! o, }Logic check, 逻辑检查
( h) c2 D" ]: R9 ?+ t4 t" V- u0 b7 qLogistic distribution, 逻辑斯特分布1 _4 W3 j$ }$ M1 M2 k4 H1 [$ |
Logit transformation, Logit转换' i$ x- W T: A. }6 i* k
LOGLINEAR, 多维列联表通用模型
* ^* V' e. }0 m9 E9 s4 u3 CLognormal distribution, 对数正态分布' L' [+ v* v& v* Q
Lost function, 损失函数! ~: w+ r' A' n4 n# S$ ]2 [
Low correlation, 低度相关
! b" t2 W r# }" z; yLower limit, 下限
& _4 e$ q/ Y, m1 D: _; H KLowest-attained variance, 最小可达方差0 P* K4 ~! G& `+ _( q
LSD, 最小显著差法的简称! r: C! M: c+ f4 L8 y+ S7 c3 q
Lurking variable, 潜在变量7 Z6 `& Z, J I# O5 m
Main effect, 主效应
1 d+ Z, g) b8 T- ~- n1 [; b# m" ^Major heading, 主辞标目& C' }# `; l5 k& h
Marginal density function, 边缘密度函数
4 G2 |, M) F3 q; AMarginal probability, 边缘概率0 R9 P! {1 i/ C4 _
Marginal probability distribution, 边缘概率分布/ k( d# z8 `3 i
Matched data, 配对资料 l* m2 g5 E' K8 J
Matched distribution, 匹配过分布
: Q6 [# f) d$ l6 v `$ rMatching of distribution, 分布的匹配
. S" s l% V& iMatching of transformation, 变换的匹配
- s! _7 a& p# r4 tMathematical expectation, 数学期望+ j6 t6 ]* T9 U8 H0 A
Mathematical model, 数学模型& T2 l7 P- x. I& r; p' `! t
Maximum L-estimator, 极大极小L 估计量
D2 j% e1 L: Y2 I jMaximum likelihood method, 最大似然法
H& t3 `& A: y/ w- l& G# u! HMean, 均数
6 f2 ]; S. K. i9 l# z2 xMean squares between groups, 组间均方) ~5 p1 C: P& ~6 n# s$ n
Mean squares within group, 组内均方
: P# q7 B* \$ `Means (Compare means), 均值-均值比较
6 G& Q8 p; \ e9 m/ vMedian, 中位数
% A0 y) R2 s$ ^. pMedian effective dose, 半数效量
# K1 d1 S2 B/ W# jMedian lethal dose, 半数致死量; K5 p# H7 k8 H! A: f2 N# {7 A& X
Median polish, 中位数平滑3 f4 h# h$ y( j9 G/ k
Median test, 中位数检验
2 Y% R3 ~, W% e. bMinimal sufficient statistic, 最小充分统计量
6 f0 V2 ^6 x* J% s- LMinimum distance estimation, 最小距离估计' W1 N7 ]( E. F. |. @; Q7 a
Minimum effective dose, 最小有效量
2 q% i, m3 u6 A8 eMinimum lethal dose, 最小致死量! q |! ?* w8 c/ V' C, e
Minimum variance estimator, 最小方差估计量' f( j k7 G& M( Z& H4 o
MINITAB, 统计软件包! `1 w9 x: F0 t# ^4 H5 C9 G
Minor heading, 宾词标目8 P4 n r9 h8 ^0 x7 \: e
Missing data, 缺失值
?- C. I" M1 I2 h7 QModel specification, 模型的确定" o- i% f: S8 d/ H# f; ^9 G
Modeling Statistics , 模型统计4 @5 D9 W1 h9 g( u: y) s# G6 a! H: V
Models for outliers, 离群值模型
8 x- z) D# n, p, ?9 dModifying the model, 模型的修正
& c l& n* U1 bModulus of continuity, 连续性模- y0 P9 j% q1 R5 Q% L2 X- C
Morbidity, 发病率
! S5 r; J' |6 ~5 r: h5 \- lMost favorable configuration, 最有利构形5 g. } z* w5 U0 M% F3 O+ n7 O5 M
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
) B. x, a; v" zMultinomial Logistic Regression , 多项逻辑斯蒂回归
) G! |2 E3 O+ |' C7 L+ K* B/ VMultiple comparison, 多重比较8 _. _- U8 Q4 j& q! k# d' L# O- @/ o: M0 H
Multiple correlation , 复相关9 a1 }3 S$ L1 f: z. D
Multiple covariance, 多元协方差6 I* l" A- ]% S% L0 b
Multiple linear regression, 多元线性回归
5 ]( L, ^, h) U& X. \* P- ]Multiple response , 多重选项
9 h) i& p1 p. hMultiple solutions, 多解$ |# o7 r2 n4 J& X% D. c
Multiplication theorem, 乘法定理% ], n9 b9 V; y+ l
Multiresponse, 多元响应6 T. F& N+ S& f: t! S
Multi-stage sampling, 多阶段抽样
: t; u* [- c9 G5 X l6 UMultivariate T distribution, 多元T分布
4 i& i( @* W% |$ | P2 lMutual exclusive, 互不相容
8 D, `& g2 j8 TMutual independence, 互相独立
6 E1 M1 X& H% S# U ANatural boundary, 自然边界
) G4 ^+ ?- H; P) FNatural dead, 自然死亡
4 J6 s2 k% @$ _+ c2 W) VNatural zero, 自然零/ p3 _, c3 m" Y1 ~, _4 B) a; U+ Z
Negative correlation, 负相关: ]% s. `2 p' y: k& T4 o
Negative linear correlation, 负线性相关
' B8 Y6 x1 x* o1 z" rNegatively skewed, 负偏$ d% e, \3 H: @, ^9 a
Newman-Keuls method, q检验
4 Q8 r' \6 L9 b% K5 h b; |# xNK method, q检验
) z; G# M" f1 u8 x' i! X/ Q2 t% b' oNo statistical significance, 无统计意义
$ M% }1 a: {/ ?/ z: C5 h9 wNominal variable, 名义变量! @% c7 t$ G$ |# _1 o
Nonconstancy of variability, 变异的非定常性0 s* p' \2 X, W+ Q$ _ |* }
Nonlinear regression, 非线性相关" v2 H' C: j+ H) K9 s) I8 F
Nonparametric statistics, 非参数统计
) `( R p. \* L/ c5 X5 oNonparametric test, 非参数检验
* T% z5 C2 O9 @3 M8 \Nonparametric tests, 非参数检验; m5 s" g) D, ?; z7 m. ~* h
Normal deviate, 正态离差
" O! B; \* H! z. {1 o6 ~2 x) f9 `Normal distribution, 正态分布
& t/ u! r' t* }) @; c5 @$ e* @Normal equation, 正规方程组/ X$ `" d) o: s
Normal ranges, 正常范围- ^* [. a! h+ L% p8 c: \
Normal value, 正常值
! d2 T" }! I1 [% n! e BNuisance parameter, 多余参数/讨厌参数7 A( X ]& K$ G6 T" Y% K6 k! D
Null hypothesis, 无效假设 $ P% v- e( W' _( f) P5 z
Numerical variable, 数值变量, r0 ]7 ?' m. x0 ~; l% `" Q
Objective function, 目标函数; x0 o- s- p/ y" g* n: k2 n
Observation unit, 观察单位
+ {9 }; ^0 @/ _* f6 @Observed value, 观察值
% @, D0 s* T! B) I; P) B" ^One sided test, 单侧检验
$ f3 X, R7 y# z) Y+ W# B% LOne-way analysis of variance, 单因素方差分析
/ M5 t' V8 t8 x& hOneway ANOVA , 单因素方差分析
( a" H" r& v$ G- U" u- pOpen sequential trial, 开放型序贯设计
( ]8 W, C0 W- ~7 g6 X N! pOptrim, 优切尾/ @* Q0 X1 u! u! t1 v: T
Optrim efficiency, 优切尾效率 }# V1 q% L/ J4 P6 R! ?) R6 r" Q
Order statistics, 顺序统计量
0 @7 U9 Z3 C/ D! ]8 N$ \Ordered categories, 有序分类5 \5 \% O) u5 B0 R! y
Ordinal logistic regression , 序数逻辑斯蒂回归
2 t5 \0 `4 A/ ?! kOrdinal variable, 有序变量
, l; n0 d1 H; l* nOrthogonal basis, 正交基
. F6 F* i8 _) x. COrthogonal design, 正交试验设计
7 S/ [$ S7 ^1 k2 q. d8 GOrthogonality conditions, 正交条件
$ R- t; F' s0 H5 q/ [ORTHOPLAN, 正交设计
% ]# S' q d, w! z# M1 R% l1 wOutlier cutoffs, 离群值截断点
* _0 K& Q, s% IOutliers, 极端值0 R( {/ a; ^+ q2 Q0 h
OVERALS , 多组变量的非线性正规相关 1 U ] M: p8 r7 h
Overshoot, 迭代过度
- Q4 i/ A7 H2 J# o8 J; w* y2 VPaired design, 配对设计. V: C5 t B" z
Paired sample, 配对样本
" M+ n+ r8 ^# x) N1 oPairwise slopes, 成对斜率2 X/ \& v5 n/ j0 M, U1 b3 v3 y
Parabola, 抛物线% o- Z8 R+ I e
Parallel tests, 平行试验: n1 I2 c3 C: }# a3 j' Y
Parameter, 参数4 `3 x) B" V* F4 ]+ ~) J
Parametric statistics, 参数统计
E5 n H: t$ u0 ]) B" J. ]6 m& i2 QParametric test, 参数检验3 d( G: U& s/ p( X3 k
Partial correlation, 偏相关2 S6 x7 l; {& d* y9 a& B' L/ [. \
Partial regression, 偏回归
6 I- n" [, p4 r, w/ Y. APartial sorting, 偏排序
$ l' ]4 P* h! OPartials residuals, 偏残差
7 Q6 D& W: w" O. _Pattern, 模式
/ k3 W- b. R* N# U( F" A) xPearson curves, 皮尔逊曲线
) H! R: O6 r$ R$ u" q# |Peeling, 退层
. w$ r5 m2 P1 W0 Q# _1 l- H5 t* uPercent bar graph, 百分条形图
2 j/ e' n7 D& u8 B! cPercentage, 百分比
; c8 [ a0 t! A; d: gPercentile, 百分位数+ E0 L+ } i9 H! L1 g9 S
Percentile curves, 百分位曲线+ p2 T8 z' F( ^8 }* I2 e, R
Periodicity, 周期性
, O4 W. J6 ^: l, }Permutation, 排列( x% p2 u9 |0 Z) C7 U! m
P-estimator, P估计量
+ u& Z& n( S7 z8 g TPie graph, 饼图
f7 D3 C8 g& d5 S4 fPitman estimator, 皮特曼估计量$ t) e- ~ b) K( q: B1 W' j
Pivot, 枢轴量
2 S6 T* ]0 r$ t1 sPlanar, 平坦
) y% ]& e! ^) g; i& yPlanar assumption, 平面的假设
3 G: M6 E* e" L O) \% LPLANCARDS, 生成试验的计划卡
& H2 Z8 [/ A2 s: J% @+ I4 hPoint estimation, 点估计+ Q% P- S# n' ~; u9 Y! w3 N
Poisson distribution, 泊松分布
+ A* f* J# K. a# WPolishing, 平滑- T# }4 t" N. g5 E% U6 |1 `) S$ m
Polled standard deviation, 合并标准差
8 n- L. l' U* o+ N3 B. IPolled variance, 合并方差# t% d! P2 m$ q9 V* d) F4 M
Polygon, 多边图8 z, Y. \( V* v6 d7 B/ v& Y
Polynomial, 多项式
& y! ~$ L5 T; ^' Y/ }Polynomial curve, 多项式曲线
- a: s7 P: y/ V" PPopulation, 总体2 B4 y! E1 q2 r m/ K7 W8 P) W* @
Population attributable risk, 人群归因危险度
% J; \! t7 ~2 ~' u8 lPositive correlation, 正相关# v8 v0 b; X8 C' r( _ e _* y
Positively skewed, 正偏
* K+ ]9 H4 _2 J3 iPosterior distribution, 后验分布
6 ^' U/ z" e. x3 G5 T4 q* B4 h4 BPower of a test, 检验效能
0 L, ?3 n# C& i/ d0 V6 }Precision, 精密度
5 u' G6 X# h3 `" \) k6 ]* d* A7 v4 pPredicted value, 预测值
0 M" A0 Z6 p8 O2 J6 `- ZPreliminary analysis, 预备性分析
5 |# p" {) \+ h" @9 z' hPrincipal component analysis, 主成分分析& `2 w5 C$ C" r1 H# K4 X
Prior distribution, 先验分布
% ^! H4 r' j1 S* S8 d' \. P) J4 @- `Prior probability, 先验概率
1 ^7 e" F4 D1 F; a" hProbabilistic model, 概率模型; G+ ^ s' l" r. G* W
probability, 概率
8 n4 ~# P2 d$ O9 m' k2 g" OProbability density, 概率密度
1 M; R4 G$ L% n1 s" cProduct moment, 乘积矩/协方差
: U* R' Q# c* |) r$ x, HProfile trace, 截面迹图
7 u6 X6 w3 P) [9 ~: [# f7 KProportion, 比/构成比
: Q3 a# m1 { F8 y0 g4 [- tProportion allocation in stratified random sampling, 按比例分层随机抽样
, {! d" p! C" tProportionate, 成比例
9 Z. m5 [1 [' c; X& ZProportionate sub-class numbers, 成比例次级组含量
! N3 ?3 `. D8 o! N9 G, j# u* nProspective study, 前瞻性调查4 ?7 P. A. @7 H. [: m
Proximities, 亲近性
Z4 j6 ?7 g& @" T1 B0 B5 D8 @Pseudo F test, 近似F检验8 F! u9 o3 Z$ Z) m% V9 {
Pseudo model, 近似模型
' b3 k: K& v* M6 w, v2 vPseudosigma, 伪标准差
# T' M* e' a+ x6 l: ]* XPurposive sampling, 有目的抽样# `& _) U/ r, e. w* K* B8 Z
QR decomposition, QR分解$ n4 ?- U1 @4 J1 y6 c5 {
Quadratic approximation, 二次近似# D# \* k. ~7 R) }
Qualitative classification, 属性分类
* b7 ]# |5 H9 `4 w+ |1 cQualitative method, 定性方法
( U9 D7 |$ H4 J' {+ AQuantile-quantile plot, 分位数-分位数图/Q-Q图9 H5 O( N' t! z; g& r
Quantitative analysis, 定量分析* P: f6 Z4 E- y7 s( J- {$ A% d+ K m
Quartile, 四分位数0 n* W( A# I1 [! z5 V9 \4 T- ]
Quick Cluster, 快速聚类
# l: f4 C9 i& Q+ m) DRadix sort, 基数排序
# k+ ^2 C7 k4 O: P. d% M+ aRandom allocation, 随机化分组9 M9 o! C6 P' B0 S4 J. h5 f/ I
Random blocks design, 随机区组设计2 r" t5 x4 ?& g3 K+ ~! }
Random event, 随机事件
5 J) q" o5 M) ?, u! y8 x! ~Randomization, 随机化
( ?0 }6 q* g. K& HRange, 极差/全距. y! ^& r. u: W( X0 p% d5 R& w
Rank correlation, 等级相关$ c9 T- v, G8 ~! _
Rank sum test, 秩和检验9 o* _0 a2 |7 _- f, h1 F5 A8 b- k
Rank test, 秩检验
4 ~; P0 c y$ hRanked data, 等级资料9 Z+ ^9 ^/ r+ z% E9 S! D, T( C
Rate, 比率! l& Y4 I a6 `4 i9 k8 r
Ratio, 比例
h' d8 ~3 j5 a% z8 c( l0 NRaw data, 原始资料0 A0 l* s" M! g0 w8 `+ G
Raw residual, 原始残差3 S& y$ r/ k; _8 y- k9 X
Rayleigh's test, 雷氏检验
. M! Y* C; l/ ~* X* v0 LRayleigh's Z, 雷氏Z值 s9 Y* ], i' g! R
Reciprocal, 倒数3 K) E% ~# D& v* c8 w
Reciprocal transformation, 倒数变换
8 c+ F9 y% @" V LRecording, 记录5 T5 x4 l1 H+ D$ z$ U+ t
Redescending estimators, 回降估计量
) n0 `, L" W, I* ]+ E/ IReducing dimensions, 降维6 H8 T5 I: v, r: V# s2 _
Re-expression, 重新表达* w$ S; z) S+ m, \# Y
Reference set, 标准组
) J+ h' `. k- W$ M- YRegion of acceptance, 接受域
, k( C6 V( r+ r: w* VRegression coefficient, 回归系数, N, }/ |6 R# {/ j. T9 Q. ?' ~
Regression sum of square, 回归平方和* s1 T. p2 o, F! o p( ~6 N
Rejection point, 拒绝点4 F# M6 ]5 O$ f$ A: E
Relative dispersion, 相对离散度
' f9 e8 S: J+ k4 n6 v: T# GRelative number, 相对数3 a' m" Z/ X7 f/ o
Reliability, 可靠性% r. S* U: G8 k: |% ]. {) W n
Reparametrization, 重新设置参数
# V! O, N' @8 rReplication, 重复
" D# k; J! w- n1 x; ~- dReport Summaries, 报告摘要1 N+ U2 o3 f/ N
Residual sum of square, 剩余平方和# L) ^6 n& W/ a
Resistance, 耐抗性
2 L- Q* A: D$ S3 E! {$ r# ]Resistant line, 耐抗线4 ^ C8 V S- ?3 I
Resistant technique, 耐抗技术& F5 N3 ]9 [+ I: K# Q7 G, L# q
R-estimator of location, 位置R估计量
+ |# \3 @0 J0 Q$ sR-estimator of scale, 尺度R估计量 ]7 C" C* Y/ @1 [
Retrospective study, 回顾性调查8 C* O. e( }+ k [* x3 _
Ridge trace, 岭迹, N$ n+ K0 a7 r) z& }
Ridit analysis, Ridit分析
( m: Z) s5 m/ w! m" I- sRotation, 旋转) x3 G+ O6 ?" Q
Rounding, 舍入
8 ~2 a0 x% o" K9 z/ V, RRow, 行+ C1 }: m8 Q X% ~, ]% j
Row effects, 行效应
% t0 N) @' c2 P- L% Z& WRow factor, 行因素. K o2 P( X9 O& z* t
RXC table, RXC表
/ H7 \6 R( A( M7 t* }. w. lSample, 样本9 B: v9 Q* s |) P# K
Sample regression coefficient, 样本回归系数
: V4 n" s% i7 [Sample size, 样本量
! P. o! [0 b4 G4 ]. t0 m C* rSample standard deviation, 样本标准差
, w; V# b/ p! v; f' T' c8 Y0 p sSampling error, 抽样误差
8 }6 m! {' U( Y) _+ ~SAS(Statistical analysis system ), SAS统计软件包$ L# b1 b; w# P
Scale, 尺度/量表
3 o/ `) ] l( G" zScatter diagram, 散点图, w/ x! \6 y6 Q( a6 {% d9 M
Schematic plot, 示意图/简图" e4 N6 }: ?/ ?+ E2 n6 `6 ]0 H8 `) {
Score test, 计分检验
4 `5 [+ `6 x7 V+ D9 J0 `Screening, 筛检
. x; ]. t$ r9 {! x% E, i( O, n2 |SEASON, 季节分析
0 b q, r5 b) G# _: l! @Second derivative, 二阶导数
( x5 u: q- I+ m( @2 \+ WSecond principal component, 第二主成分
; M* c! P' G4 l% ^4 |SEM (Structural equation modeling), 结构化方程模型
* y7 d# t& ?( e% y U1 rSemi-logarithmic graph, 半对数图
0 [( X+ @% b5 @4 eSemi-logarithmic paper, 半对数格纸, d9 E$ B6 U o
Sensitivity curve, 敏感度曲线8 ` v; A! r) F0 `2 b: j
Sequential analysis, 贯序分析
7 z# `7 @5 p) Y0 lSequential data set, 顺序数据集; c, s$ {( h5 V9 c! d5 m8 ]7 W4 H8 _6 H
Sequential design, 贯序设计
( ]4 M$ t a1 {1 A3 A rSequential method, 贯序法9 u/ v( z: ^$ ]! G+ f' l8 c# m
Sequential test, 贯序检验法 ]. h$ B H1 N$ C! k; M4 ?7 Q
Serial tests, 系列试验7 Q1 ]: ^" g7 a- G9 p3 ^0 n4 c
Short-cut method, 简捷法 8 {% K3 m9 V; m- [" O
Sigmoid curve, S形曲线
( E7 e: @# h6 E0 wSign function, 正负号函数1 p# _6 ^/ l, Q8 f' X% x2 R# `
Sign test, 符号检验4 `& ~% ]' z0 B+ E3 b- v
Signed rank, 符号秩+ b1 r" }7 ^# Q ~# B; s4 F
Significance test, 显著性检验% I/ u: d" Z/ V8 ?( x: g# ?- }
Significant figure, 有效数字; q/ K2 d" b. y' o
Simple cluster sampling, 简单整群抽样
* b! G/ c S) u9 ~0 V# Z2 ^Simple correlation, 简单相关' o' u6 @: ?' l7 \7 ]1 I7 }
Simple random sampling, 简单随机抽样
& T6 f5 Q ^! y8 i2 z# ESimple regression, 简单回归4 V/ w" B0 w* s+ t2 a# U7 ?2 q
simple table, 简单表2 K9 Y" ^9 D# X6 m5 U. C
Sine estimator, 正弦估计量
/ L2 U$ v6 G/ k8 D3 F# l2 }Single-valued estimate, 单值估计
" n1 f- w9 m7 c& D* l* gSingular matrix, 奇异矩阵
C( [* R, H7 a7 F; O lSkewed distribution, 偏斜分布
* }3 G& a( T0 P* A2 E# k {0 xSkewness, 偏度0 r- P6 l V9 v, w( O
Slash distribution, 斜线分布4 a- W* O1 |7 q. Q, ?( S
Slope, 斜率. ~! o1 Q' y, e' v" }! q
Smirnov test, 斯米尔诺夫检验
& y' B, a- q% _0 }( qSource of variation, 变异来源
# l q- E2 Y" J6 C+ ZSpearman rank correlation, 斯皮尔曼等级相关7 N/ l: V, q$ @+ [3 F6 A
Specific factor, 特殊因子
) D1 c' F. X/ |6 }' A/ w! X4 LSpecific factor variance, 特殊因子方差) O+ _4 {2 J3 d' a/ [3 }+ A* J
Spectra , 频谱" u9 P! s6 @! \1 q) x
Spherical distribution, 球型正态分布. R, n* G, H& h+ Q" e9 a5 H
Spread, 展布6 d& g2 u1 ~' d. d3 @; _
SPSS(Statistical package for the social science), SPSS统计软件包4 Q. N; ]. m- \% r
Spurious correlation, 假性相关
1 e" C+ o' Q, s# S# ~4 qSquare root transformation, 平方根变换
, Z) z. z$ a+ A5 _- b# oStabilizing variance, 稳定方差
3 k1 a9 O, C- U/ o8 H4 QStandard deviation, 标准差* L; s* K/ N( \
Standard error, 标准误
1 j3 p/ Y( r" R, `Standard error of difference, 差别的标准误7 v: G/ q0 k' b
Standard error of estimate, 标准估计误差
Y3 i$ ~1 w, n* JStandard error of rate, 率的标准误
/ p7 T t, D$ HStandard normal distribution, 标准正态分布
- J# h) ?; A# d4 M7 C' m! JStandardization, 标准化
, ?9 ?( p ^% _0 [. d$ vStarting value, 起始值
7 A8 U* O; S' M5 aStatistic, 统计量
L: [/ z4 _, ?Statistical control, 统计控制
- u$ D/ f4 ^$ _ S5 d( T) o9 VStatistical graph, 统计图
& }: y/ I0 \* s9 qStatistical inference, 统计推断: i6 y W0 W$ ^
Statistical table, 统计表
. E l1 |9 w6 u4 d8 R/ pSteepest descent, 最速下降法8 l, _2 C" Y( ]( h& X* F
Stem and leaf display, 茎叶图6 y2 q+ ]% }8 {; g; ~6 x) }
Step factor, 步长因子* S% i- V) u& A# ~# ]) U
Stepwise regression, 逐步回归! p0 W8 w: R6 i1 ]
Storage, 存: d1 G4 O2 `* |$ u4 d# R* M
Strata, 层(复数)
; B( H. U; X( x2 d- }0 z) Z# EStratified sampling, 分层抽样% K( F @7 |' M# k( o
Stratified sampling, 分层抽样/ \+ { {8 v: W7 V$ `7 D
Strength, 强度
' U" V+ @! n7 q5 j2 a8 R: J9 CStringency, 严密性- Z8 v& @& h; C- l9 h+ e8 v
Structural relationship, 结构关系
k# E4 D* ~7 A4 D- HStudentized residual, 学生化残差/t化残差! p+ H% x+ C C. A
Sub-class numbers, 次级组含量
* t, H k, V( t ]- Z# bSubdividing, 分割, I3 N" U# [/ m) u _" ]
Sufficient statistic, 充分统计量$ i0 Q. C3 T8 Y/ t, Q
Sum of products, 积和5 w# f7 I8 O2 Q& {9 w# A) P& Z
Sum of squares, 离差平方和
+ L! B, H+ m* j5 c" vSum of squares about regression, 回归平方和
# C; X9 m8 O" X0 cSum of squares between groups, 组间平方和
( R) T4 v" k" h1 |Sum of squares of partial regression, 偏回归平方和; c4 f8 @' Z2 d4 T$ l
Sure event, 必然事件
: a9 v: ~6 @$ V5 H" x! PSurvey, 调查
2 {+ o' N) N/ f5 W% Y+ USurvival, 生存分析- x3 e. p% V+ q: D8 @
Survival rate, 生存率
: h7 M( U8 V* @5 ~Suspended root gram, 悬吊根图
( T5 Y9 i- P5 B% V4 J. e$ USymmetry, 对称0 q) z$ I+ q0 p; F+ e
Systematic error, 系统误差3 L8 a9 z2 t6 @
Systematic sampling, 系统抽样3 ~; G, x7 P$ R4 W- {* n
Tags, 标签& |& ~* Q& _5 Q& q2 A0 n( O& }. e
Tail area, 尾部面积- ]; N( F$ v" h" P% I
Tail length, 尾长+ h7 S8 ~0 G0 P! T/ | Q q8 r
Tail weight, 尾重7 y' s5 }/ z8 l( z* D- i3 E8 W
Tangent line, 切线
( z& m6 z; D5 R: ?. vTarget distribution, 目标分布% ?! m9 e0 o# I) q& j+ l3 w
Taylor series, 泰勒级数& L* H1 W6 a& @& _7 }
Tendency of dispersion, 离散趋势# [7 N& P I4 x; R" r% V: ?
Testing of hypotheses, 假设检验- [4 ~& w& ~0 q
Theoretical frequency, 理论频数) K( x# X9 L& [8 u; P/ R2 {
Time series, 时间序列
6 ~6 n& D: B. j; N0 W8 nTolerance interval, 容忍区间
$ a$ ~ Z. A" x ?Tolerance lower limit, 容忍下限' H& m( W5 [( l n+ S9 H
Tolerance upper limit, 容忍上限
9 Z {( j* g: ?6 P! N# D9 HTorsion, 扰率; B; Z) H3 s8 g7 r) y, W
Total sum of square, 总平方和
9 j% a! o Y# P9 L* `5 STotal variation, 总变异
* Q% Q/ O% }6 g( \- jTransformation, 转换' ~3 ~# z1 ~5 X" D5 y# r) Q* K3 u
Treatment, 处理9 t0 k& L7 S! f8 g
Trend, 趋势
, l& \ R; \/ Y6 Q8 qTrend of percentage, 百分比趋势
2 S1 `* N, m1 u: gTrial, 试验
( `* r0 m5 ` aTrial and error method, 试错法3 A9 g( u g [+ C1 c* D9 C( U
Tuning constant, 细调常数
4 L% M, {" }9 g/ V2 f' L. {$ X+ xTwo sided test, 双向检验7 _" v- {5 s7 h4 p. J, c8 g5 R
Two-stage least squares, 二阶最小平方
F3 S6 Y# f. W1 }1 STwo-stage sampling, 二阶段抽样% [+ C/ O5 }8 J7 Z0 A
Two-tailed test, 双侧检验, V" a2 ^ l# j% r' H
Two-way analysis of variance, 双因素方差分析
' b5 ^4 s" r8 c8 y; _Two-way table, 双向表
. ]8 Q0 I: [/ e( c. _Type I error, 一类错误/α错误3 r$ m6 u- T6 U4 U' R" B! R* h
Type II error, 二类错误/β错误! t- c" T+ ?) r
UMVU, 方差一致最小无偏估计简称 e1 K, L2 B' |( ~
Unbiased estimate, 无偏估计
1 J0 T! O& _3 c( OUnconstrained nonlinear regression , 无约束非线性回归
( T t. Z0 C6 H% C/ }* hUnequal subclass number, 不等次级组含量5 L4 d7 f* o" P3 p& M; R! b
Ungrouped data, 不分组资料
- w s0 y* i z6 ?- ]4 _" E, jUniform coordinate, 均匀坐标* P8 \, {. \- K- {# h f$ `
Uniform distribution, 均匀分布7 K7 o8 s0 J* P
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计1 ]0 l- r0 ]2 N. N/ T- N+ \( ^( g) \
Unit, 单元6 p. B4 F* A0 w1 r2 E" G# \1 a
Unordered categories, 无序分类
' ]" ~2 u _* a3 G' DUpper limit, 上限2 f6 W) \* W7 N5 w6 U. M4 I% [& m
Upward rank, 升秩4 H/ A4 j2 {3 l# B( W
Vague concept, 模糊概念
) p n' u* Z! H/ `: u! DValidity, 有效性% U: o$ l/ m; E% P% r3 ~( T
VARCOMP (Variance component estimation), 方差元素估计7 O0 u# [/ m( z) z" ]
Variability, 变异性
7 A- @. c1 J! p6 eVariable, 变量
- t3 m0 N8 ^4 B8 F* @* `Variance, 方差4 o2 R! w8 Q. U5 e
Variation, 变异4 v' N) @8 i% V
Varimax orthogonal rotation, 方差最大正交旋转! V- O* p7 z, S9 y0 g* h7 z! u1 P
Volume of distribution, 容积4 H1 z8 r w2 u/ y4 y/ R: A ]2 @
W test, W检验
h. ~6 k, ~, l2 R" DWeibull distribution, 威布尔分布: t: p' T# `0 P! r6 v
Weight, 权数
3 ]+ W, I H2 i+ W& {! Y" |; C3 Y9 WWeighted Chi-square test, 加权卡方检验/Cochran检验
& h, n& i. L" m( t! }. pWeighted linear regression method, 加权直线回归
' J! r+ Y1 p+ g2 dWeighted mean, 加权平均数* z3 ~% T3 A& O+ t9 T
Weighted mean square, 加权平均方差 @% X, o, W! q2 s6 t
Weighted sum of square, 加权平方和
3 S; c3 }$ l4 U# v, T5 k0 YWeighting coefficient, 权重系数
' k- l& b+ l+ _" t' c0 fWeighting method, 加权法
8 s8 O1 F @, v, {3 r+ X) _W-estimation, W估计量
7 [3 N! J0 r* x+ M" U/ GW-estimation of location, 位置W估计量& k7 X- Z4 s. D m; A1 g) Y2 X& d: Q0 h
Width, 宽度
$ ]1 Y5 V) |- J- D! ?. E/ \Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验2 u+ O/ p) h8 d2 o9 M
Wild point, 野点/狂点$ q( o1 A% ]$ y( {5 C
Wild value, 野值/狂值 X- `8 \4 `: Q; r: I. y# j" S
Winsorized mean, 缩尾均值
' c1 h; c, C; ~) @. XWithdraw, 失访 6 \( D6 ^3 x: W
Youden's index, 尤登指数
/ \# U% D7 n, _Z test, Z检验; z( m. z0 L9 X# b! w
Zero correlation, 零相关* x6 _% Y& G( [0 P) D
Z-transformation, Z变换 |
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